Abstract

Everyone in this rapid evolution generation makes use of online resources. There is a huge amount of textual content available online from several sources, including social media apps, e-commerce sites, movie recommendation system, etc. Everyone in the modern society provides a variety of reviews for a specific product or item. An effective and smart technique is required that can analyze and provide the polarity of this textual data. since it is impossible to manually review such a vast volume of user-generated data. For this user-generated data, automatic sentiment classification is possible using a variety of tools and methods. Opinion mining and sentiment classification benefit from the dependable and accuracy of machine learning. Moreover, the sentiment analysis and evaluation process are fraught with difficulties. These complexities make it difficult to interpret sentiments accurately and figure out the right sentiment polarity. This article describes an overview on sentiment analysis(SA) applications, challenges, and issues encountered by researchers, with the goal of providing a systematic review on sentiment analysis and related areas for future research.

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